US7308072B2 - Device and method for x-ray scatter correction in computer tomography - Google Patents
Device and method for x-ray scatter correction in computer tomography Download PDFInfo
- Publication number
- US7308072B2 US7308072B2 US11/154,727 US15472705A US7308072B2 US 7308072 B2 US7308072 B2 US 7308072B2 US 15472705 A US15472705 A US 15472705A US 7308072 B2 US7308072 B2 US 7308072B2
- Authority
- US
- United States
- Prior art keywords
- scatter
- ray
- detector
- distribution
- projection images
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related, expires
Links
- 238000012937 correction Methods 0.000 title claims abstract description 66
- 238000002591 computed tomography Methods 0.000 title claims abstract description 17
- 238000000034 method Methods 0.000 title claims description 32
- 238000011156 evaluation Methods 0.000 claims abstract description 19
- 238000000342 Monte Carlo simulation Methods 0.000 claims abstract description 11
- 230000003993 interaction Effects 0.000 claims abstract description 5
- 230000005855 radiation Effects 0.000 claims description 88
- 238000009826 distribution Methods 0.000 claims description 75
- 230000006870 function Effects 0.000 claims description 13
- 238000004422 calculation algorithm Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 6
- 210000000988 bone and bone Anatomy 0.000 description 26
- 238000004364 calculation method Methods 0.000 description 23
- 238000012545 processing Methods 0.000 description 20
- 210000004872 soft tissue Anatomy 0.000 description 19
- 239000000463 material Substances 0.000 description 17
- 238000010586 diagram Methods 0.000 description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 8
- 238000007408 cone-beam computed tomography Methods 0.000 description 7
- 230000001419 dependent effect Effects 0.000 description 7
- 238000005259 measurement Methods 0.000 description 6
- 238000004088 simulation Methods 0.000 description 6
- 238000001228 spectrum Methods 0.000 description 6
- 230000008901 benefit Effects 0.000 description 5
- 210000001519 tissue Anatomy 0.000 description 5
- 238000001914 filtration Methods 0.000 description 4
- 230000011218 segmentation Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 239000000203 mixture Substances 0.000 description 3
- 230000006978 adaptation Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000004069 differentiation Effects 0.000 description 2
- 238000005315 distribution function Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000002601 radiography Methods 0.000 description 2
- UGJCNRLBGKEGEH-UHFFFAOYSA-N sodium-binding benzofuran isophthalate Chemical compound COC1=CC=2C=C(C=3C(=CC(=CC=3)C(O)=O)C(O)=O)OC=2C=C1N(CCOCC1)CCOCCOCCN1C(C(=CC=1C=2)OC)=CC=1OC=2C1=CC=C(C(O)=O)C=C1C(O)=O UGJCNRLBGKEGEH-UHFFFAOYSA-N 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 230000007480 spreading Effects 0.000 description 2
- 238000003892 spreading Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 230000001629 suppression Effects 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- VVQNEPGJFQJSBK-UHFFFAOYSA-N Methyl methacrylate Chemical compound COC(=O)C(C)=C VVQNEPGJFQJSBK-UHFFFAOYSA-N 0.000 description 1
- 229920005372 Plexiglas® Polymers 0.000 description 1
- 239000004698 Polyethylene Substances 0.000 description 1
- 230000002745 absorbent Effects 0.000 description 1
- 239000002250 absorbent Substances 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000002583 angiography Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000001174 ascending effect Effects 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 239000013078 crystal Substances 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000005538 encapsulation Methods 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000013152 interventional procedure Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 229920003023 plastic Polymers 0.000 description 1
- 239000004033 plastic Substances 0.000 description 1
- -1 polyethylene Polymers 0.000 description 1
- 229920000573 polyethylene Polymers 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- WFKWXMTUELFFGS-UHFFFAOYSA-N tungsten Chemical compound [W] WFKWXMTUELFFGS-UHFFFAOYSA-N 0.000 description 1
- 229910052721 tungsten Inorganic materials 0.000 description 1
- 239000010937 tungsten Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/005—Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computed tomography [CT]
- A61B6/032—Transmission computed tomography [CT]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
- A61B6/5258—Devices using data or image processing specially adapted for radiation diagnosis involving detection or reduction of artifacts or noise
- A61B6/5282—Devices using data or image processing specially adapted for radiation diagnosis involving detection or reduction of artifacts or noise due to scatter
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
- G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
- G01N23/046—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material using tomography, e.g. computed tomography [CT]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/42—Arrangements for detecting radiation specially adapted for radiation diagnosis
- A61B6/4291—Arrangements for detecting radiation specially adapted for radiation diagnosis the detector being combined with a grid or grating
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2223/00—Investigating materials by wave or particle radiation
- G01N2223/40—Imaging
- G01N2223/419—Imaging computed tomograph
Definitions
- the invention relates to a device for computer tomography with a radiographic source, a detector and an evaluation unit arranged after the detector which uses the projection images supplied by the detector and taken from a variety of projection directions to determine scattering information, and on the basis of the scattering information, corrects the x-ray scatter component in the projection images.
- the invention further relates to a method with x-ray scatter correction for computer tomography as well as to a method for obtaining scattering information.
- a device and a method of this type with scattering correction are known from U.S. Pat. No. 5,666,391 A.
- the known device and the known method allow x-ray scatter to be corrected within the framework of computer tomography.
- CT Computer Tomography
- a serious problem is however the x-ray scatter generated in the object or patient under examination, the intensity of which can reach and in some cases even exceed the order of magnitude of the unscattered, direct primary radiation.
- One of the consequences is a significant deterioration of the quantitative tissue density reconstruction, another is that artifacts are produced. Errors of several hundred 100 HU can thus occur and dark shadows or bar artifacts between strongly absorbent structures can lead to incorrect diagnoses.
- a basic disadvantage of the method known from U.S. Pat. No. 5,666,391 and of the known device relates to accuracy and lies in the fact that projection data is corrected directly without recourse to the reconstructed image (volume) and the information available within it about the scatter object is not used in the correction.
- An object of the invention is to specify a device and a method with which an improved method of x-ray scatter correction as regards accuracy compared to the prior art can be performed.
- the device for computer tomography has a radiographic source, a detector and an evaluation unit arranged after the detector.
- the evaluation unit determines a three-dimensional object model differentiated in accordance with scatter characteristics and, depending on the object model, reads out from a data memory scatter information of which the parameters depend on the object model.
- the scatter information is in particular scatter distributions determined in advance using Monte Carlo simulations in which multiple interactions of the photons with the object to be examined are taken into account.
- the solution proposed here has the following advantages: No additional measurement is needed. Furthermore no mechanical modification is necessary and no additional devices are needed for the CBCT scanner.
- the purely computational correction uses information from the reconstructed volume and by virtue of this feedback is more accurate than methods which only operate directly on the projection data without recourse to the image volume. Finally the correction algorithm can be reduced to a fraction of the computation requirements for a standard reconstruction without correction.
- the scatter information is scatter distributions which describe the scatter-induced distribution of the radiation emitted from the radiographic source and directed to a specific detector element on adjacent detector elements.
- the evaluation unit determines the x-ray scatter proportion in an area of the projection image in which the evaluation unit computes and adds the scatter radiation contributions of the surrounding image areas.
- the individual x-ray scatter contributions are in this case a function of the non-scattered x-ray components assigned to the adjacent image areas in each case.
- a number of elementary image elements of the detector are assembled into shared image areas and the scatter correction computed for the individual image areas. This offers the advantage of being able to reduce the computing overhead for scatter correction.
- the evaluation unit segments the object model of the object to be examined in that, depending on scatter parameters of the material covered by the volume element, the evaluation unit assigns the volume element to a scatter category from a set of scatter categories determined in advance.
- This measure serves to simplify the setting of parameters for the scatter information, since in this case the scatter information only has to be calculated for the predetermined discrete scatter categories.
- the object model used to calculate the scatter correction exhibits a low discrete local resolution on the object model created after the evaluation unit has run the scatter correction.
- the x-ray scatter correction itself can be performed in a different way.
- the evaluation unit it is possible, for the evaluation unit to perform an x-ray scatter correction on the projection images and with the aid of x-ray scatter corrected projection images to create a volume image with full local resolution in each case.
- the procedure is a good idea if the x-ray scatter distribution contains higher-frequency local frequency components
- FIG. 1 a side view of a computer tomography unit
- FIG. 2 an overview diagram of the sequence of the scatter correction
- FIG. 3 a presentation of a segmented reprojection for an object to be examined inhomogeneously
- FIG. 4 a diagram of an object model used to calculate the x-ray scatter distribution function
- FIG. 5 a more detailed diagram of an embodiment of scatter correction
- FIG. 6 a more detailed diagram of the execution sequence of a further embodiment of scatter correction
- FIG. 7 a diagram in which the distribution of the primary radiation and the secondary radiation is shown for a specific object model
- FIG. 8 a diagram in which the distribution of the primary radiation and the secondary radiation is shown for an object model with material distribution which can be inverted by comparison with FIG. 7 ;
- FIG. 9 a diagram in which x-ray scatter distribution functions are shown for different material compositions of an object to be examined.
- FIG. 1 shows a computer tomography device 1 which is used to examine a patient 2 .
- the patient 2 is on a support bed 3 which stands on a floor 4 .
- On the floor 4 there is also a stand 5 with a holder 6 for a C-arm 7 which has a radiographic source 9 on one of its ends 8 and on the other end 10 has a detector 11 .
- the C-arm 7 can be moved in the holder 6 in a circular direction 12 .
- the C-arm 7 can be swiveled around a pivot axis 13 .
- CT-gantry encircling frame
- radiation 14 is emitted from the radiographic source 9 which will also be referred to as source radiation 14 below.
- a component of the radiation 14 designated as primary radiation 15 passes through the patient 2 without changing its direction and reaches the detector 11 .
- a further component of the radiation 14 designated as secondary radiation or scatter radiation 16 undergoes scattering at least once on its way from the radiographic source 9 to the detector 11 and is deflected from its original direction.
- scattering is to be taken to mean any type of interaction between the radiation 14 and the material lying on the path between radiographic source 9 and detector 11 , through which a change in the spread direction of the photons of the radiation 14 is brought about.
- a data recording 18 is undertaken, during which a series of projection images 19 are recorded from different projection directions.
- the projection images 19 must be subjected to a scatter correction 20 .
- an image reconstruction 21 a three-dimensional volume image 22 largely free of artifacts of the object to be examined is produced.
- the data for the scatter correction 20 is obtained as follows: First the required scatter correction is estimated or the projection images 19 are included in their uncorrected state for image reconstruction 21 .
- the initially uncorrected volume image 22 is then converted into a scatter model 23 which forms the basis for image data calculation 24 .
- SBF scatter beam spread functions
- the projection images 19 are then subjected to scatter correction 20 with the aid of the scatter data. After a renewed image reconstruction 21 a new scatter-corrected volume image is created 22 .
- the SBF 25 depends on the recording parameters and on object parameters. Typical recording parameters are: Tube voltage, pre-filtering, air gap, SID (source—Image distance), collimation (detector inclusion), anti-scatter grid (or not).
- the object parameter is the (to be reconstructed) spatial distribution (of the attenuation coefficient) of the tissue in the patient 2 .
- the SBF 25 depends especially on the generally inhomogeneous distribution in accordance with FIG. 3 of the tissue along the rays of the x-ray radiation 14 , with it essentially being a matter of the different proportions of the bone tissue 27 or at least bone-type substance and soft tissue 28 .
- SBF atlas a table created in advance is available with the aid of which it is possible, for the specific given recording conditions, to determine the associated SBF 25 sufficiently accurately for each inhomogeneous distribution of bone tissue 27 and soft tissue 28 .
- This might be done by interpolation in the SBF atlas or by semi-empirical transformations for parameters, on which the SBF is only slightly dependent or for which functional dependencies are known. The latter is for example the case in relation to the SID.
- a segmentation algorithm is required, with which—using something like a threshold criterion—a separate presentation of the bone volume and of the soft tissue volume can be created from the three-dimensional object volume.
- a further differentiation, for example between metal 29 or air 30 is basically possible.
- a reprojection algorithm with the aid of which the length of an x-ray beam 14 corresponding to the recording geometry of the individual contributions of the bone tissue 27 and of the soft tissue 28 to the attenuation can be computed and summed in a localized way.
- a reconstruction algorithm in order to perform an object volume reconstruction from cone beam projection data for example a method based on filtered back projections.
- Such methods are described for example in L. A. FELDKAMP, L. C. DAVIS, J. W. KRESS: Practical cone-beam algorithm. in: J. Opt. Soc. Amer. A, Vol. 6, 1984, pages 612-619 and in K. WIESENT, K. BARTH, N. NAVAB u. a.: Enhanced 3-D-Reconstruction Algorithm for C-Arm system Suitable for Interventional Procedures. in: IEEE Trans. Med. Imaging, Vol. 19, No. 5, May 2000, pages 391-403.
- the processing is undertaken at different levels in a number of nested loops, in ascending order: (I) the level of the object volume, (II), (II′) the level of the CT projections and (III) the level of the individual beam or individual detector areas.
- the air gap 33 is the gap between the detector 11 and the object to be examined.
- the air gap 33 has a not-insignificant effect on the intensity of the x-ray scatter since only the x-ray scatter proportion which is directed to the detector 11 reaches the detector 11 . As the gap between detector 11 and the object to be examined increases, the intensity of the x-ray scatter thus reduces.
- Reprojection also called forwards projection, is the computer simulation of the passage of a beam of x-ray radiation 14 from the focal point of the radiographic source 9 through the object volume to the detector 11 .
- Beam in this context should be taken to mean a conical beam of x-ray radiation 14 which is directed to a specific detector pixel with each cone beam being represented by a ray iray in the sense of geometrical optics
- segmented reprojection is intended to express that the reprojection is applied to the segmented object volume for bone tissue 27 and soft tissue 28 and in addition that the ray of the x-ray radiation is divided up into a number of segments on its way through the object volume. This will be explained in greater detail below.
- the segmented reprojection is executed for each CT projection direction iphi (0 to ⁇ 360 degrees) and for each detector pixel 32 (after the binning), with the detector pixel 32 being identified by an index iray which designates the associated ray of the x-ray radiation 14 .
- the segmented reprojection includes the following operations:
- the ray configuration f is naturally also dependent on the energy spectrum, especially tube voltage selected, the filter used and further parameters. These are specific recording parameters but remain constant during data acquisition.
- the lookup in the SBF atlas is undertaken for each ray iray.
- An SBF 25 is a two-dimensional function or a two-dimensional field of the row coordinates and column coordinates on the detector 11 and can be stored in relation to the binned detector pixel index units or also in finer discretization.
- Each SBF 25 is concentrated around a center, the relevant ray of the x-ray radiation 14 or the relevant detector pixel 32 with the coordinates (0,0), and drops sharply with the distance from the center of the ray.
- the distance from the center in both coordinate directions is identified by a pair of indexes (jx, jy) in which case for simplicity's sake we will use binned detector pixel units below.
- the SBF 25 is a type of point or line image function, where “point” or “line” is to be replaced by “ray”
- P iray, iphi
- I 0 the intensity of the source radiation 14 emitted by the radiographic source 9 , which would be registered without attenuation in the detector pixel 32 .
- Each ray(index) iray can be identified by a row/column index pair(ix, iy) of a detector pixel 32 .
- the index iray in (Eq. 3) and (Eq. 4) can thus be replaced by the equivalent index pair (ix, iy).
- the x-ray scatter distribution S is thus produced by a type of location-dependent folding of the primary radiation distribution P with the location-independent scatter contributions described by SBFs 25 .
- the x-ray scatter distribution is relatively smooth and thus has a low-frequency Fourier spectrum. To eliminate any possible high-frequency error components induced by processing steps (1) to (6) a two-dimensional smoothing is to be recommended.
- the x-ray scatter correction described below is executed on the fine or on the coarsened d etector pixel grid.
- a further improvement, if desired, can be achieved by repeating the processing steps (1) to (9).
- SBF (f ⁇ ) also contains the dependency of the x-ray energy spectrum of the tube voltage voltage, of the pre-filtering, of radiation-sensitive detector material (for example scintillation crystal) and the dependency on whether an anti-scatter grid is used or not and if necessary which anti-scatter grid is used.
- radiation-sensitive detector material for example scintillation crystal
- a ray configuration of this type, which is actually three-dimensional, is shown in FIG. 4 in a two-dimensional cross-section.
- the SBF 25 practically no longer depends on the micro configuration of the distribution of bone tissue 27 and soft tissue 28 within the subsection k.
- Micro configuration in this case is understood to be the distribution of bone tissue 27 and soft tissue 28 in relation to the individual binned or unbinned voxels.
- the length of the subsections 27 does not necessarily have to correspond to the length of the binned or unbinned voxels 31 . Instead it is worthwhile selecting the length of the subsections 37 in the order of magnitude of the average scatter path length which is as a rule greater than the length of the binned voxels. This will be explained in greater detail in connection with the discussion of the feasibility and the computing effort.
- the distribution of the x-ray scatter created in the scatter body is of interest in the detector level if the (unscattered) ray of the x-ray radiation 14 is focused precisely on one detector pixel 32 . If this is done consecutively for each detector pixel 32 and all associated SBFs 25 are summed, the overall x-ray scatter distribution is obtained.
- larger binned detector pixels 32 are used for calculation of the SBFs 25 (for example 1 ⁇ 1 cm 2 or 0.5 ⁇ 0.5 cm 2 ).
- the SBFs 25 generally depend on a plurality of parameters. If one wished to discretize each parameter in accordance with the micro configuration of the ray in fine steps, millions of SBFs 25 would have to be calculated. This would be barely feasible since a Monte-Carlo calculation to obtain an SBF 25 with sufficient accuracy on of a modern workstation computer takes several minutes at least. Therefore a solution must be found which on the one hand can be executed with manageable computing effort and on the other hand delivers the scatter information necessary and sufficient for scatter correction.
- the SBFs 25 are most strongly dependent on the ray configuration in the object model, meaning on the overall path length 36 of the ray in the material and of the occupation of the path length 36 by bone tissue 27 and soft tissue 14 which the ray penetrates and in which the scatter processes also occur. It is noticeable here that the scatter distribution on the detector 11 is essentially determined by scatter processes in a exit layer of the scatter body near to its surface. The thickness of this effective exit layer corresponds to around 1-2 average scatter path lengths.
- One average scatter path length is the reciprocal value of the linear attenuation coefficient. For water-like material and an energy of 70 keV this is typically about 5 cm.
- the ray length rayleng of the ray in the object i.e. the object thickness
- the ray length rayleng of the ray in the object is varied for example in the range 5 to 40 cm in steps of 5 cm.
- Each fixed ray length rayleng is subdivided into a number ksub of subsections (for example of 5 cm length or coarser in their turn).
- different pairs of “mass occupancies” length*density for bone tissue bK and soft tissue bW are varied.
- SBF atlas obtained in this way can be expanded by interpolation of the SBFs 25 for a finer parameter discretization.
- One SBF 25 stored in the SBF atlas represents one scatter category in this case.
- the Monte Carlo calculations are to be made for both cases. Since the x-ray scatter is already reduced by the grid to about 1 ⁇ 5 it may be possible to work for simulation calculations with grids with a coarser parameter discretization.
- Monte-Carlo calculations for creating the SBF atlas need only be performed once for a production series of the same type of computer tomograph, for example with the same design of x-ray tube, the same detector, similar recording geometry or the same anti-scatter grid.
- the propagation of the x-ray photons as a random process is known to be simulated with the Monte Carlo method.
- the results are affected by statistical fluctuations, depending on the method, these being smaller the greater the number of trajectories of x-ray photons which were calculated in the simulation.
- the fluctuations can be reduced by suitable averaging of the calculated SBF if for theoretical reasons the SBF must exhibit symmetry characteristics, for example rotation symmetry in the case of a lack of anti-scatter grid or asymmetry in relation to two orthogonal axes when an anti-scatter grid is present).
- the remaining rough estimates resulting from the Monte-Carlo calculation in the calculated SBFs 25 can be sufficiently eliminated by deviations of minimizing curve adaptation.
- the computing time requirements can be of the order of magnitude of weeks here, but can be significantly reduced by distributing it to a number of computers or by using more powerful computing systems with many fast processors.
- the use of greater computing power can also be employed to calculate a larger number of ray configurations with finer parameter discretization or lateral inhomogeneous ray configurations as will be explained in embodiment 4.
- Disk-shaped and cylindrical phantoms with different thicknesses or diameters made of water or plastics with physical properties similar to water (for example polyethylene or Plexiglass), are suitable.
- the beam stop method has proven itself in particular for measuring x-ray scatter.
- CT computer tomography devices
- FPD flat-panel detector
- angiography CT with C-arm and x-ray image amplifier or FPD mobile C-arm CT with x-ray image amplifier or FPD.
- Embodiment 0 is shown again in detail in FIG. 5 .
- Data recording 18 leads to projection images 19 to which scatter correction 20 will be applied.
- An image reconstruction 21 produces a volume image 22 .
- the volume image 22 is subjected to a coarsening 38 which leads to a scatter model 23 .
- the coarsening 38 corresponds to the processing step (1) in which the number of voxels 31 and of detector pixels 32 has been decimated.
- the coarsening 38 leads to the scatter model 23 on the basis of which the scatter data calculation can be performed.
- a first processing section 39 comprises the processing steps (2) to (4) described above and leads to a lookup 40 in the SBF atlas stored in data memory 26 .
- the SBFs 25 of the scatter data calculation 24 stored in the SBF atlas are made available by reading them out 41 . If necessary interpolation is performed between the stored SBFs 25 . In a second processing section 42 the processing steps (6) to (8) can then be performed.
- the lookup 40 and read out 41 correspond to the processing step (5) described above.
- scatter data 43 is present at low resolution.
- this can be converted in scatter data 45 of higher resolution. Details of the refinement 44 are described in connection with processing step (7).
- the CBCT reconstruction is performed on the original possibly fine voxel- and detector pixel grid and for all projection directions.
- the x-ray scatter is then corrected in accordance with embodiment 0 up to and including processing step (8a), with the transition to the original fine pixel grid having been completed in step (7).
- the volume reconstruction in the processing step(9) is only performed with a small number of projections.
- the number of projections can for example be reduced by a factor of 4. A greater reduction factor may also possibly be permitted. If the reconstruction of the uncorrected projection data with the reduced number is also available, an x-ray scatter correction volume is produced from the difference between corrected and uncorrected volume.
- the data recording 18 creates projection images 19 which are subjected to a high-resolution image reconstruction 46 which leads to a high-resolution uncorrected volume image 47 .
- the high-resolution uncorrected volume image 47 is subjected to the coarsening 38 and thereby converted into the scatter model 23 .
- processing sections 39 and 42 can be performed.
- scatter data 43 at low resolution is produced.
- the projection images 19 are further subjected to a coarsening 48 which leads to projection images 49 with low local resolution.
- a scatter correction 50 is undertaken, as well as a subsequent image reconstruction 51 , with the image reconstruction 51 calculating a correction volume image 52 at low resolution.
- the correction volume image 52 is thus based, as in embodiment 2, on the difference between the uncorrected projection images 49 on the basis of the scatter data 43 corrected projection images.
- a subsequent refinement 53 produces a high-resolution correction volume image 54 , which will be processed in an addition procedure 55 together with the high-resolution uncorrected volume image 47 into volume image 22 .
- the corrected volume image 22 can then be subjected to a coarsening 56 in order to create a corrected scatter model 23 which can serve as the basis for a new execution of the correction cycle shown in FIG. 6 by double arrows.
- An advantage of the third embodiment shown in FIG. 6 is that the scatter correction can be largely performed at low resolution. This reduces the computing effort significantly.
- processing step (6) is then reduce d to one folding which can be inverted with the aid of a Fourier transformation.
- iterative calculation undertaken in processing step (8) can be replaced by a deconvolution.
- the parameterization of the x-ray scatter spread functions (SBFs) 25 is further differentiated in that subsections 37 , into which the ray length 36 is subdivided, cannot just continue homogeneously, as is shown in FIG. 4 , but also inhomogeneously in a lateral spread direction at right angles to the direction of spread. Account should be taken here however of the fact that inhomogenities at a lateral distance of more than around two ray lengths have practically no influence.
- the scatter material can be “smeared” over the width of around one ray length (typically around 5 cm) in each case. Taking account of laterally inhomogeneous SBFs can above all play a part in the vicinity of the object edge where on one side no further scatter material adjoins.
- a common factor to all embodiments is that the calculation of the SBFs 25 with the aid of Monte Carlo simulations allows detailed modeling of the physical reality. Multiple scatter processes along the path of an x-ray photon and the effects of complex surfaces can especially be modeled.
- FIG. 7 shows a primary radiation distribution 57 and a secondary radiation distribution 58 along the central detector row of a 30 ⁇ 40 cm 2 flat-panel detector.
- the two distributions are each entered in arbitrary units along the x-coordinate.
- the pixels of the flat image detector each have an extent of 1 ⁇ 1 cm 2 . It has further been assumed that the flat image detector involved is a flat image detector with CsI-scintillator. The flat image detector should also no be assigned to any anti-scatter grid for echo suppression of the x-ray scatter.
- the x-ray tube is assumed to have a tungsten anode and of an x-ray voltage of 70 kV.
- the radiation emitted by the x-ray tube has been collimated to the full detector surface on the tube side.
- the gap between x-ray source and flat image detector was selected as 115 cm and the air gap between scatter body and the flat image detector as 20 cm.
- a plate-shaped spread-out scatter body was used for the simulation, in which in the ray direction 5 cm of bone preceded 20 cm of water. Typical value were used for the specification of the bones. Density 1,486 g/cm 3 , atomic proportions H: 7; O: 3.06; C: 1.92; N: 0.28; P:0.22; Ca.: 0.25.
- the primary radiation distribution 57 and the secondary radiation distribution 58 correspond to the energy values deposited in the middle detector row extending along the lengthwise side in arbitrary units.
- FIGS. 7 and 8 A comparison of the diagrams in the FIGS. 7 and 8 shows clearly that the primary radiation distributions 57 and 59 are essentially the same.
- the secondary radiation distributions 58 and 60 by contrast differ widely from each other.
- the intensity of the secondary radiation distribution 58 in the middle of the detector plane is up to 27% greater than that of the secondary radiation distribution 60 .
- FIG. 9 shows x-ray scatter spread functions 61 and 62 .
- X-ray scatter spread functions 61 and 62 were calculated by assuming a collimation of the x-ray radiation on an individual pixel with a spread of 1 ⁇ 1 cm 2 .
- the x-ray scatter spread functions 61 reflect the case in which a 5 cm layer of bone is located before a 20 cm layer of water in the radiation direction
- x-ray scatter spread function 62 reflects the case in which 5 cm bone lies behind 20 cm water in the radiation direction.
- FIGS. 7 to 9 clearly shown that in the energy range between around 60 and 150 keV, in which operations are undertaken in standard computer tomography, a pre-constructive correction of the x-ray scatter is not sufficient. This is because this type of correction would have to use the attenuation of the primary radiation as its starting point. This would however lead in the energy range of interest to unsatisfactory results. This is because the examples in FIGS. 7 and 8 T show, that with the same attenuation of the primary radiation the distribution of the secondary radiation can turn out differently depending on the properties of the material.
- the x-ray scatter can be satisfactorily corrected, since the calculation of the x-ray scatter correction can take account of the distribution of material in the object to be examined.
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Medical Informatics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- General Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Radiology & Medical Imaging (AREA)
- Pathology (AREA)
- Biomedical Technology (AREA)
- General Physics & Mathematics (AREA)
- High Energy & Nuclear Physics (AREA)
- Biophysics (AREA)
- Pulmonology (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Optics & Photonics (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Immunology (AREA)
- Apparatus For Radiation Diagnosis (AREA)
Abstract
Description
-
- i. Determination of an
entry voxel 34 and of anexit voxel 35 in the object volume, that is the location of the entry and the exit of the ray iray on the surface of thepatient 2, and thereby theray length 36 in the object: irayleng. - ii. Subdivision of the
ray length 36 intoiray_sub subsections 37. The subdivision is to be adapted to the discretization of the SBF atlas (see below). - iii. Reprojection through the segmented bone and soft tissue volume, so that for each subsection i=1 . . . iray_sub the ray path length irayleng of the relevant (logarithmic) attenuation contribution of bone and soft tissue substance ibK(i) and ibW (i) is determined. The attenuation contributions are defined here as:
- i. Determination of an
f(iray,iphi)=(iairgap,irayleng,((ibW(i), ibK(i)), i=1. . . iray_sub, . . . ) (eq. 1)
SBF(f^)=SBF(airgap,rayleng,((bW(k), bK(k)), k=1 . . . kray_sub), spectrum, . . . ) (eq. 2)
dS(jx, jy; iray;iphi)=SBFI(f(irayiphi);(jx, jy)) (Eq. 3)
P(iray, iphi)=exp(−p(iray,iphi)) (Eq. 4).
dS(jx, jy; kray;iphi)*P(kx, ky, iphi) (Eq. 5)
with jx=ix−kx, jy=iy−ky at the point iray=(ix, iy).
T=P+S
where the terms have the following meanings:
- T Distribution if the total radiation (measured uncorrected projection images 19)
- P Primary radiation distribution (initially unknown, but sought)
- S Secondary radiation distribution (initially unknown but estimated with the proposed model).
P(ix, iy;iphi)=T(ix, iy; iphi)−S(ix, iy; iphi) (Eq. 7)
to estimate the primary radiation distribution.
P=T/(1+S/P) (Eq. 8)
S=S(P)
P=T−S(P)
p(ix, iy; iphi)=−log P(ix, iy; iphi), (Eq. 9)
and a new object volume reconstruction is then performed from this corrected CBCT projection data.
SBF(f^)=SBF(airgap,rayleng, ((bW(k), bK(k)), k=1 . . . ksu b), voltage, . . . ) (Eq. 2)
-
- (1) the adaptive calculation of x-ray scatter distribution from an already reconstructed object volume in an efficient manner.
- (2) the use of (inhomogeneous) Scatter-Beam-spread-Functions (SBF) which have already been calculated in advance and which thus only need to be accessed, saving on computing time, in the form of a large table (SBF atlas);
- (3) covering essentially all recording parameters occurring (spectrum, air gap, SID, grid, etc.) and object parameters (combination of bone and soft tissue and further parameters) in the SBF atlas.
- (4) a further feature of the method described is, that within the framework of segmented reprojection direct coupling with a hardening correction is produced almost automatically since the individual categories of scatter materials, for
example bone tissue 27 andsoft tissue 28 can be assigned the known actual attenuation coefficients.
Claims (10)
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE102004029009.1 | 2004-06-16 | ||
DE102004029009A DE102004029009A1 (en) | 2004-06-16 | 2004-06-16 | Apparatus and method for scattered radiation correction in computer tomography |
Publications (2)
Publication Number | Publication Date |
---|---|
US20060008046A1 US20060008046A1 (en) | 2006-01-12 |
US7308072B2 true US7308072B2 (en) | 2007-12-11 |
Family
ID=35507849
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US11/154,727 Expired - Fee Related US7308072B2 (en) | 2004-06-16 | 2005-06-16 | Device and method for x-ray scatter correction in computer tomography |
Country Status (2)
Country | Link |
---|---|
US (1) | US7308072B2 (en) |
DE (1) | DE102004029009A1 (en) |
Cited By (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060120507A1 (en) * | 2004-11-26 | 2006-06-08 | Thomas Brunner | Angiographic x-ray diagnostic device for rotation angiography |
US20080013673A1 (en) * | 2004-06-16 | 2008-01-17 | Ernst-Peter Ruhmschopf | Apparatus and Method for Scatter Correction in Projection Radiography |
US20090202127A1 (en) * | 2006-06-22 | 2009-08-13 | Koninklijke Philips Electronics N.V. | Method And System For Error Compensation |
US20090225932A1 (en) * | 2008-02-27 | 2009-09-10 | Lei Zhu | Cone-beam CT imaging scheme |
US20100002830A1 (en) * | 2006-08-01 | 2010-01-07 | Koninklijke Philips Electronics N. V. | Stereo tube computed tomography |
US20100119139A1 (en) * | 2006-06-22 | 2010-05-13 | Koninklijke Philips Electronics N. V. | Method and system for error compensation |
US20100140485A1 (en) * | 2008-12-10 | 2010-06-10 | General Electric Company | Imaging system and method with scatter correction |
US8483471B2 (en) | 2011-06-30 | 2013-07-09 | General Electric Company | Method and system for scatter correction in X-ray imaging |
US8989469B2 (en) | 2010-12-20 | 2015-03-24 | The Board Of Trustees Of The Leland Stanford Junior University | Systems and methods for simultaneous acquisition of scatter and image projection data in computed tomography |
US10722205B2 (en) * | 2016-11-07 | 2020-07-28 | Shenzhen Institutes Of Advanced Technology | Method and apparatus for optimizing blocking grating for cone beam CT image scattering correction |
US10820878B2 (en) * | 2017-03-01 | 2020-11-03 | Ibex Innovations Limited | Apparatus and method for the correction of scatter in a radiographic system |
US11992356B2 (en) | 2018-08-31 | 2024-05-28 | Ibex Innovations Limited | X-ray imaging system |
Families Citing this family (33)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060259282A1 (en) * | 2003-03-14 | 2006-11-16 | Failla Gregory A | Deterministic computation of radiation transport for radiotherapy dose calculations and scatter correction for image reconstruction |
WO2007035775A2 (en) * | 2005-09-19 | 2007-03-29 | Feng Ma | Imaging system and method utilizing primary radiation |
US7283605B2 (en) * | 2006-01-14 | 2007-10-16 | General Electric Company | Methods and apparatus for scatter correction |
DE102006019923A1 (en) | 2006-04-28 | 2007-11-15 | Siemens Ag | Method for scattered radiation correction in X-ray CT and X-ray CT for the application of this method |
DE102006021373A1 (en) | 2006-05-08 | 2007-11-15 | Siemens Ag | X-ray diagnostic device |
JP2007300964A (en) * | 2006-05-08 | 2007-11-22 | Ge Medical Systems Global Technology Co Llc | Radiographic equipment and radiography method |
US7519143B2 (en) * | 2006-06-29 | 2009-04-14 | General Electric Company | Method and system for generating a scatter corrected X-ray image |
DE102006045722B4 (en) * | 2006-09-27 | 2014-11-27 | Siemens Aktiengesellschaft | Method of correcting scattered radiation in projection radiography and computer tomography and apparatus therefor |
WO2008059400A2 (en) | 2006-11-16 | 2008-05-22 | Koninklijke Philips Electronics N.V. | Computer tomography (ct) c-arm system and method for examination of an object |
DE102006062319B4 (en) * | 2006-12-27 | 2008-09-18 | Siemens Ag | Method for reducing scattered artefacts in reconstructed CT image data and X-ray CT system with arithmetic unit for performing this method |
US7804936B2 (en) * | 2007-06-28 | 2010-09-28 | Siemens Medical Solutions Usa, Inc. | Dose-guided radiation therapy using cone beam CT |
DE102007056980B4 (en) | 2007-11-27 | 2016-09-22 | Siemens Healthcare Gmbh | Method and device for computed tomography |
US8976928B2 (en) * | 2009-09-02 | 2015-03-10 | Shimadzu Corporation | Radiographic apparatus and image acquiring method |
EP2545855B1 (en) * | 2011-07-13 | 2016-09-07 | General Electric Company | System and method of locating an X-ray imaging apparatus and corresponding X-ray imaging apparatus. |
JP2013079825A (en) * | 2011-10-03 | 2013-05-02 | Hitachi Ltd | X-ray ct image reconstruction method, and x-ray ct device |
US20130304409A1 (en) * | 2012-05-10 | 2013-11-14 | Board Of Regents, The University Of Texas System | Methods for validating plastic scintillating detectors and applications of same |
WO2015058702A1 (en) * | 2013-10-23 | 2015-04-30 | 曹红光 | Photon count-based radiation imaging system, method, and apparatus |
CN104970815B (en) * | 2014-04-04 | 2018-03-16 | 北京纳米维景科技有限公司 | X-ray imaging system and method based on raster phase contrast and photon counting |
GB201318998D0 (en) * | 2013-10-28 | 2013-12-11 | Kromek Ltd | Method and apparatus for the scanning of contained materials |
DE102015216780A1 (en) | 2014-09-29 | 2016-03-31 | Siemens Aktiengesellschaft | Method and device for determining a scattered radiation contribution for a scattered radiation correction of an X-ray image |
KR20170080594A (en) | 2014-10-04 | 2017-07-10 | 아이벡스 이노베이션스 리미티드 | Improvements relating to scatter in x-ray apparatus and methods of their use |
WO2016141956A1 (en) | 2015-03-06 | 2016-09-15 | Ge Sensing & Inspection Technologies Gmbh | Imaging system and method with scatter correction |
CN104840211B (en) * | 2015-05-18 | 2018-12-25 | 上海联影医疗科技有限公司 | A kind of scatter correction method and device of projected image |
CN106256327B (en) * | 2016-08-11 | 2019-07-30 | 天津金曦医疗设备有限公司 | A kind of cone beam computed tomography (CT) scattering correction system and bearing calibration based on big data |
JP6707046B2 (en) * | 2017-03-17 | 2020-06-10 | 富士フイルム株式会社 | Tomographic image processing apparatus, method and program |
US11864940B2 (en) | 2017-07-04 | 2024-01-09 | Eos Imaging | Method of radiography of an organ of a patient |
CN108254395B (en) * | 2017-12-28 | 2023-10-13 | 清华大学 | Scanned image correction device, method and mobile scanning equipment |
JP2019180906A (en) * | 2018-04-11 | 2019-10-24 | 富士フイルム株式会社 | Image processing apparatus, radiographic imaging system, image processing method, and image processing program |
KR20200092747A (en) | 2019-01-25 | 2020-08-04 | 삼성전자주식회사 | Method for processing of a x-ray image and apparatus for processing a x-ray image |
KR20200095859A (en) * | 2019-02-01 | 2020-08-11 | 삼성전자주식회사 | Method for processing of a x-ray image and apparatus for processing a x-ray image performing the same |
US10846855B2 (en) * | 2019-04-24 | 2020-11-24 | Hiwin Technologies Corp. | Method for converting scan information of a computed tomography scanner into bone parameters |
JP7022268B2 (en) * | 2019-08-01 | 2022-02-18 | 恵一 中川 | X-ray cone beam CT image reconstruction method |
CN116531015B (en) * | 2023-07-04 | 2023-10-03 | 中国科学院深圳先进技术研究院 | Image reconstruction method, device, electronic equipment and storage medium |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4918713A (en) * | 1986-02-18 | 1990-04-17 | Kabushiki Kaisha Toshiba | System and method for correcting for scattered x-rays |
US5666391A (en) | 1995-06-26 | 1997-09-09 | Siemens Aktiengesellschaft | X-ray examination system with identification of and compensation for subject-produced scattered radiation to reduce image artifacts |
US5905809A (en) * | 1993-11-10 | 1999-05-18 | U.S. Philips Corporation | Method of and apparatus for computed tomography |
US6134297A (en) * | 1998-12-09 | 2000-10-17 | Advanced Optical Technologies, Inc. | Apparatus and method for removing scatter from an x-ray image using two-dimensional detectors and a single-energy spectrum x-ray source |
US6256367B1 (en) * | 1997-06-14 | 2001-07-03 | General Electric Company | Monte Carlo scatter correction method for computed tomography of general object geometries |
US6618466B1 (en) | 2002-02-21 | 2003-09-09 | University Of Rochester | Apparatus and method for x-ray scatter reduction and correction for fan beam CT and cone beam volume CT |
US6639964B2 (en) * | 2000-09-27 | 2003-10-28 | Koninklijke Philips Electronics N.V. | Device and method for forming a computed X-ray tomogram with scatter correction |
US7145980B2 (en) * | 2003-02-13 | 2006-12-05 | Kabushiki Kaisha Toshiba | X-ray diagnosis apparatus and method for obtaining an X-ray image |
-
2004
- 2004-06-16 DE DE102004029009A patent/DE102004029009A1/en not_active Withdrawn
-
2005
- 2005-06-16 US US11/154,727 patent/US7308072B2/en not_active Expired - Fee Related
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4918713A (en) * | 1986-02-18 | 1990-04-17 | Kabushiki Kaisha Toshiba | System and method for correcting for scattered x-rays |
US5905809A (en) * | 1993-11-10 | 1999-05-18 | U.S. Philips Corporation | Method of and apparatus for computed tomography |
US5666391A (en) | 1995-06-26 | 1997-09-09 | Siemens Aktiengesellschaft | X-ray examination system with identification of and compensation for subject-produced scattered radiation to reduce image artifacts |
US6256367B1 (en) * | 1997-06-14 | 2001-07-03 | General Electric Company | Monte Carlo scatter correction method for computed tomography of general object geometries |
US6134297A (en) * | 1998-12-09 | 2000-10-17 | Advanced Optical Technologies, Inc. | Apparatus and method for removing scatter from an x-ray image using two-dimensional detectors and a single-energy spectrum x-ray source |
US6639964B2 (en) * | 2000-09-27 | 2003-10-28 | Koninklijke Philips Electronics N.V. | Device and method for forming a computed X-ray tomogram with scatter correction |
US6618466B1 (en) | 2002-02-21 | 2003-09-09 | University Of Rochester | Apparatus and method for x-ray scatter reduction and correction for fan beam CT and cone beam volume CT |
US7145980B2 (en) * | 2003-02-13 | 2006-12-05 | Kabushiki Kaisha Toshiba | X-ray diagnosis apparatus and method for obtaining an X-ray image |
Non-Patent Citations (6)
Title |
---|
Karl Wiesent, K. Barth, N. Navab, P. Durlak, T. Brunner, O. Schuetz and W. Seissler, "Enhanced 3-D-Reconstruction Algorithm for C-Arm Systems Suitable for Interventional Procedures", IEEE Transactions on Medical Imaging, No. 5, May 2000, pp. 391-403, vol. 19. |
L. Spies, M. Ebert, B.A. Groh, B.M. Hesse and T. Bortfeld, "Correction of Scatter in Megavoltage Cone-beam CT", Physics in Medicine and Biology, 2001, pp. 821-833, vol. 46, IOP Publishing Ltd, UK. |
L.A. Feldkamp, L.C. Davis and J.W. Kress, "Practical Cone-Beam Algorithm", J. Opt. Soc. Am. A, Jun. 1984, pp. 612-619, vol. 1, No. 6. |
Ruola Ning, Xiangyang Tang, and D.L. Conover, "X-ray Scatter Suppression Algorithm For Cone Beam Volume CT", Proceedings of SPIE 2002, pp. 774-781, vol. 4682. |
Vibeke N. Hansen, William Swindell and Philip M. Evans, "Extraction of Primary Signal From EPIDs Using Only Forward Convolution", Medical Physics, Sep. 1997, pp. 1477-1484, vol. 24, No. 9. |
Willi Kalender, "Monte Carlo Calculations of X-Ray Scatter Data for Diagnostic Radiology", Physics in Medicine and Biology, 1981, pp. 835-849, vol. 26, No. 5. |
Cited By (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20080013673A1 (en) * | 2004-06-16 | 2008-01-17 | Ernst-Peter Ruhmschopf | Apparatus and Method for Scatter Correction in Projection Radiography |
US7551716B2 (en) * | 2004-06-16 | 2009-06-23 | Siemens Aktiengesellschaft | Apparatus and method for scatter correction in projection radiography |
US7734009B2 (en) * | 2004-11-26 | 2010-06-08 | Siemens Aktiengesellschaft | Angiographic x-ray diagnostic device for rotation angiography |
US20060120507A1 (en) * | 2004-11-26 | 2006-06-08 | Thomas Brunner | Angiographic x-ray diagnostic device for rotation angiography |
US20090202127A1 (en) * | 2006-06-22 | 2009-08-13 | Koninklijke Philips Electronics N.V. | Method And System For Error Compensation |
US20100119139A1 (en) * | 2006-06-22 | 2010-05-13 | Koninklijke Philips Electronics N. V. | Method and system for error compensation |
US8000435B2 (en) * | 2006-06-22 | 2011-08-16 | Koninklijke Philips Electronics N.V. | Method and system for error compensation |
US20100002830A1 (en) * | 2006-08-01 | 2010-01-07 | Koninklijke Philips Electronics N. V. | Stereo tube computed tomography |
US7826585B2 (en) * | 2006-08-01 | 2010-11-02 | Koninklijke Philips Electronics N.V. | Stereo tube computed tomography |
US8144829B2 (en) | 2008-02-27 | 2012-03-27 | The Board Of Trustees Of The Leland Stanford Junior University | Cone-beam CT imaging scheme |
US20090225932A1 (en) * | 2008-02-27 | 2009-09-10 | Lei Zhu | Cone-beam CT imaging scheme |
US20100140485A1 (en) * | 2008-12-10 | 2010-06-10 | General Electric Company | Imaging system and method with scatter correction |
US8184767B2 (en) | 2008-12-10 | 2012-05-22 | General Electric Company | Imaging system and method with scatter correction |
US8989469B2 (en) | 2010-12-20 | 2015-03-24 | The Board Of Trustees Of The Leland Stanford Junior University | Systems and methods for simultaneous acquisition of scatter and image projection data in computed tomography |
US8483471B2 (en) | 2011-06-30 | 2013-07-09 | General Electric Company | Method and system for scatter correction in X-ray imaging |
US10722205B2 (en) * | 2016-11-07 | 2020-07-28 | Shenzhen Institutes Of Advanced Technology | Method and apparatus for optimizing blocking grating for cone beam CT image scattering correction |
US10820878B2 (en) * | 2017-03-01 | 2020-11-03 | Ibex Innovations Limited | Apparatus and method for the correction of scatter in a radiographic system |
US11992356B2 (en) | 2018-08-31 | 2024-05-28 | Ibex Innovations Limited | X-ray imaging system |
Also Published As
Publication number | Publication date |
---|---|
US20060008046A1 (en) | 2006-01-12 |
DE102004029009A1 (en) | 2006-01-19 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US7308072B2 (en) | Device and method for x-ray scatter correction in computer tomography | |
US7760848B2 (en) | Method and system for generating a multi-spectral image of an object | |
CN108292428B (en) | System and method for image reconstruction | |
US10139354B2 (en) | Spectral X-ray imaging | |
Sisniega et al. | Monte Carlo study of the effects of system geometry and antiscatter grids on cone‐beam CT scatter distributions | |
Duvauchelle et al. | A computer code to simulate X-ray imaging techniques | |
US10713823B2 (en) | Image reconstructing apparatus and image reconstructing method | |
US8532350B2 (en) | Dose reduction and image enhancement in tomography through the utilization of the object's surroundings as dynamic constraints | |
US6507633B1 (en) | Method for statistically reconstructing a polyenergetic X-ray computed tomography image and image reconstructor apparatus utilizing the method | |
Rinkel et al. | A new method for x-ray scatter correction: first assessment on a cone-beam CT experimental setup | |
US7751525B2 (en) | Method for correcting x-ray scatter in projection radiography and computer tomography | |
US10593070B2 (en) | Model-based scatter correction for computed tomography | |
US8090182B2 (en) | Image reconstruction device, image reconstruction method, image reconstruction program, and CT apparatus | |
US8290116B2 (en) | Imaging apparatus including correction unit for scattered radiation | |
JP2009529394A (en) | How to reconstruct image functions from radon data | |
US11419566B2 (en) | Systems and methods for improving image quality with three-dimensional scout | |
Sun et al. | Correction for patient table‐induced scattered radiation in cone‐beam computed tomography (CBCT) | |
Wiegert et al. | Model based scatter correction for cone-beam computed tomography | |
Wu et al. | Estimating scatter from sparsely measured primary signal | |
Wiegert | Scattered radiation in cone beam computed tomography: analysis, quantification and compensation | |
Liu et al. | Impact of bowtie filter and detector collimation on multislice CT scatter profiles: a simulation study | |
Seeram et al. | Computed tomography: Physical principles, instrumentation, and quality control | |
EP3404618B1 (en) | Poly-energetic reconstruction method for metal artifacts reduction | |
Zeng et al. | Digital tomosynthesis aided by low-resolution exact computed tomography | |
Wiegert et al. | Scattered radiation in flat-detector based cone-beam CT: analysis of voxelized patient simulations |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: SIEMENS AKTIENGESELLSCHAFT, GERMANY Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:RUHRNSCHOPF, ERNST-PETER;REEL/FRAME:017030/0467 Effective date: 20050616 |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |
|
FPAY | Fee payment |
Year of fee payment: 4 |
|
FPAY | Fee payment |
Year of fee payment: 8 |
|
AS | Assignment |
Owner name: SIEMENS HEALTHCARE GMBH, GERMANY Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:SIEMENS AKTIENGESELLSCHAFT;REEL/FRAME:039271/0561 Effective date: 20160610 |
|
FEPP | Fee payment procedure |
Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY |
|
LAPS | Lapse for failure to pay maintenance fees |
Free format text: PATENT EXPIRED FOR FAILURE TO PAY MAINTENANCE FEES (ORIGINAL EVENT CODE: EXP.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY |
|
STCH | Information on status: patent discontinuation |
Free format text: PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362 |
|
FP | Lapsed due to failure to pay maintenance fee |
Effective date: 20191211 |